The disclosure relates, in general, to targeted depletion of nucleic acids and, more particularly, to a system and method for degrading selected nucleic acids polymers amongst a broader population of nucleic acids.
Whole transcriptome sequencing, also known as RNA-sequencing or RNA-seq, is a useful technique for characterizing the total gene expression of a biological sample. In this technique, RNA (either total or poly-A selected) is converted into cDNA using reverse transcriptase, followed by second-strand synthesis, addition of sequencing adapters, and high-throughput sequencing. One challenge associated with this approach is that only a very few genes (e.g., less than about ten) account for the vast majority of transcripts expressed in any particular tissue or cell type. As a result, the major portion of a given set of sequencing reads are derived from the most highly expressed genes, whereas a small portion of the sequencing reads are derived from the genes having the lowest expression levels. For example, ribosomal RNA (rRNA) can represent 90% or more of the material in a human total RNA sample. For experiments where the remaining 10% or less of the material in the sample may be relevant for a given experiment, the presence of rRNA can consume costly sequencing reagents, obscure the presence of low expression level transcripts, decrease experimental throughput, the like, or combinations thereof. The aforementioned approach to RNA-seq is therefore inefficient for studying the expression patterns and transcript structures of lowly expressed genes that may have important biological functions. Accordingly, what is needed is a new experimental approach that mitigates the detrimental effects that highly abundant transcripts can have on the efficient analysis of RNA.